Accounting & Finance FinTech and Financial Intelligence
Executive Certificate in AI and Deep Learning in Quantitative Finance
- Course Code
- Application Code
- Study mode
- Start Date
- 12 Apr 2022 (Tue)
- Next intake(s)
- Aug 2022
- 2 months to 3 months
- Course Fee
- HK$9500 per programme
- Excel has somewhat artificial Human Intelligence for data automation...
The recent advances in Big Data and AI have major impact on the investment...
Suppose your manager is considering how to promote certain product combinations...
Our professional lecturer will discuss the algorithms of deep learning (e.g., Convolution Neural Networks, Recurrent Neural Networks and Long Short Term Memory), as well as AI applications in quantitative finance and trading. Welcome for your online application!
*With effect from 17 January 2022 (Monday), HKU SPACE will follow The University of Hong Kong (HKU) in introducing enhanced COVID-19 control measures in accordance with public health policies.
*From 17 January 2022 (Monday), anyone wishing to enter HKU or HKU SPACE campuses will need either to be fully vaccinated or take weekly COVID self-tests. For the details of the enhanced measures, visit this link (https://hkuspace.hku.hk/news/detail/enhanced-covid-19-control-measures-at-hku-space/).
This programme aims to provide students with knowledge about Artificial Intelligence and Deep Learning in Quantitative Finance as well as their latest developments and applications to finance and investment. It covers various learning algorithms and neural networks as well as machine intelligence to facilitate finance and investment decision making.
On completion of this programme, students should be able to:
- Identify the latest development of AI and Deep Learning in Quantitative Finance;
- examine common learning algorithms and neural networks to facilitate investment decision making;
- illustrate the learning algorithms and neural networks using computation tools;
- discuss the applications of AI and Deep Learning in the finance services sector.
(1) Mr. Ken Liu, co-founder and CTO of Datatact Ltd, a startup focus on AI, Machine Learning and Big Data analytics. He is a hands on expert in his specialized area for over 10 years. Prior to Datatact, Ken worked at Citi, HSBC, Goldman Sachs, Deutsche Bank and Credit Suisse as Algo-Trading developer. Ken earned a Master in Computer Science from USC and a Bachelor in Computer Science from University of Warwick.
(2) Dr. Simon Yiu, IT Department Head of a financial institution in Hong Kong, has handled many FinTech initiatives and projects, such as Algo trading, finance big data analytics, Robo-advisors and so on. Before that, he also worked for AI, and Machine learning startup as co-founder and CTO which located at a Hong Kong Science Park and participated at the University organized Entrepreneurship Center in 2010, focusing on AI, Machine Learning, Big Data analytics and Natural language processing. Furthermore, he has hands-on programming experiences in FinTech areas for over 10 years. Simon earned a Doctoral Degree in Business Administration from the City University of Hong Kong and a Master Degree in Data Science and Business Statistics from The Chinese University of Hong Kong.
|Application Code||1980-EP159A||Apply Online Now|
|Apply Online Now|
Days / Time
- Saturday, 1:00pm - 7:00pm
- Kowloon Learning Centre
- Hong Kong Island Learning Centre
(1) Introduction to AI and Deep Learning in Quantitative Finance
- Overview of the latest technological developments
- Big Data and FinTech
- Cloud computing and 5G
- AI, Machine Learning and Deep Learning
- Introduction to computation tools in Quantitative Finance
- Python Programming Language
- Scikit-learn for AI and Machine Learning
- TensorFlow, Keras and PyTorch for Deep Learning
- Emerging Trends in AI, Deep Learning and FinTech
(2) Learning Algorithms and Machine Intelligence
- Supervised learning: penalized regression, support vector machine, k-nearest neighbor, classification and regression tree, ensemble learning, and random forest
- Unsupervised learning: principal components analysis, k-means clustering, and hierarchical clustering
- Reinforcement learning: deep reinforcement learning, deep Q-Learning
- Deep learning: Convolution Neural Networks (CNN), Recurrent Neural Networks (RNN) and Long Short Term Memory (LSTM)
- Cognitive analytics: Natural Language Processing (NLP), Computational Linguistics
- Algorithms on graphs: social networks, link analysis
(3) Applications of AI and Deep Learning in Quantitative Finance
- Fintech Disruption: a glimpse into the future
- Big and Alternative data powered Investment Management: stock selection (forecast combinations, feature engineering)
- Natural Language Processing: chatbots and sentiment analysis on corporate earnings, news and social media
- Reinforcement Learning: automated strategy development in algorithmic trading
- Anomaly Detection: Bankruptcy Prediction and Risk Management
- Wealth Management: Robo-advisors and the future of Digital and Virtual Banking
Assessment method: two in-class exercises + group project presentation
2022 April intake :
|1||12 Apr 22 (Tue)||19:00 - 10:00|
|2||14 Apr 22 (Thu)||19:00 - 10:00|
|3||19 Apr 22 (Tue)||19:00 - 10:00|
|4||21 Apr 22 (Thu)||19:00 - 10:00|
|5||26 Apr 22 (Tue)||19:00 - 10:00|
|6||28 Apr 22 (Thu)||19:00 - 10:00|
|7||3 May 22 (Tue)||19:00 - 10:00|
|8||5 May 22 (Thu)||19:00 - 10:00|
|9||10 May 22 (Tue)||19:00 - 10:00|
|10||12 May 22 (Thu)||19:00 - 10:00|
Remarks : Tentative timetable is subject to change and course commencement is subject to sufficient enrollment numbers
Applicants shall hold:
a) a bachelor’s degree awarded by a recognized University or equivalent; or
b) an Associate Degree/ a Higher Diploma or equivalent, and have at least 2 years of relevant working experience.
Applicants with qualifications in quantitative areas (e.g., mathematics, engineering, statistics, computer science, economics, finance) are preferred. Those with other qualifications and substantial senior level work experience will be considered on individual merit.
**Please upload copy of HKID and proof of degree while applying online.
HK$150 (student only needs to pay one time application fee for all EC in Big Data Series)Course Fee
- Course Fee : HK$9500 per programme (Course fees are subject to change without prior notice)
- Early Bird Rate : HK$8900 per programme (Early-Bird discounted fee for enrolment on/before 21 May 21)
- Alumni Rate : HK$8900 per programme (Alumni from EDEC in Big Data and FinTech Programme Series)
Online Application Apply Now
Application Form Download Application FormEnrolment Method
HKU SPACE provides 24-hour online application and payment service for students to apply to selected award-bearing programmes and to enrol in most open admission courses (courses enrolled on a first come, first served basis) via the Internet. Applicants may settle the payment by using either "PPS by Internet" (not available via mobile phones), VISA or Mastercard online. Online WeChat Pay, Online AliPay and Faster Payment System (FPS) are also available for continuing enrolment in the same programme, if online service is offered.
For first time enrolment
Complete the online application form
Applicant may click the icon on the top right hand corner of the programme/course webpage to make online application, and then follow the instructions to fill in the online application form.
Some programmes/courses may admit by selection, and may require applicants to provide electronic copy of any required documents (e.g. proof of qualification) as indicated on the programme/course webpage. Only file format in doc, docx, jpg and pdf are supported.
Make Online Payment
Pay the application or programme/course fees by either using:
"PPS by Internet" - You will need a PPS account and a PPS Internet password. For information on how to open a PPS account and how to set up a PPS Internet password, please visit http://www.ppshk.com.
*Credit Card Online Payment - Course fees can be paid by VISA or Mastercard including the “HKU SPACE Mastercard”.
* HKU SPACE Mastercard cardholders who wish to enjoy 10-month interest free instalment scheme must pay their tuition fees in person at any of our HKU SPACE Enrolment Centres.
To know more about first-time online application/enrolment and payment, please refer to the user guide of Online Application / Enrolment and Payment:
For continuing enrolment in the same programme
Selected programmes offer online continuing enrolment service. Programme staff will inform students if they offer this service and offer further enrolment details.
Online Payment can be made via "PPS by Internet" (not available via mobile phones), VISA or Mastercard, Online WeChat Pay, Online AliPay and Faster Payment System (FPS)
In Person / Mail
For first time enrolment
For first come, first served short courses, complete the Application for Enrolment Form SF26 and bring or post the completed form(s), together with the appropriate application/course fee(s) and any required supporting documents to any of the HKU SPACE enrolment centres.
[Download Enrolment Form SF26]
Award-bearing and professional courses may require other information. Forms are usually available at the enrolment centres or on request from programme staff. Bring or post the completed form(s), together with the appropriate application/course fee(s) and any required supporting documents to any of the HKU SPACE enrolment centres.
For continuing enrolment in the same programme
The standard ‘Enrolment/Payment Slip’ is designed for students of award-bearing programmes or remaining programmes in a suite of programmes requiring continuing enrolment and it applies to most programmes.
Students should complete the “Enrolment/Payment Slip” which will be made available by relevant programme staff and return the slip to any HKU SPACE enrolment centre or post it to the relevant programme staff with appropriate fee payment.
Please refer to available Payment Methods for fee payment information. If you are in doubt about the procedures, please check the individual course details, or contact our programme staff or enrolment centres.
Please note the followings for programme/course enrollment:
- Applicants should not leave the online application idle for more than 10 minutes. Otherwise, applicants must restart the application process.
- Only Early Bird Discount is supported for Online Applicants (Application). To enjoy other types of discount, please visit one of our enrolment centres.
- During the online application process, asynchronous application and payment submission may occur. Successful payment may not guarantee successful application. In case of unsuccessful submission, our programme staff will contact you shortly.
- Applicants are reminded that they should only apply for the same programme/course once through counter or online application.
- For online enrolment, a payment confirmation page would be displayed after payment has been made successfully. In addition, a confirmation email would also be sent to your email account. You are advised to keep your payment confirmation for future enquiries.
- Fees paid are not refundable except as statutorily provided or under very exceptional circumstances (e.g. course cancellation due to insufficient enrolment).
- If admission is by selection, the official receipt is not a guarantee that your application has been accepted. We will inform you of the result as soon as possible after the closing date for application. Unsuccessful applicants will be given a refund of programme/course fee if already paid.
The School provides a platform for online services for a selected range of products it offers. While every effort is made to ensure timeliness and accuracy of information contained in this website, such information and materials are provided "as is" without express or implied warranty of any kind. In particular, no warranty or assurance regarding non-infringement, security, accuracy, fitness for a purpose or freedom from computer viruses is given in connection with such information and materials.
The School (and its respective employees and subsidiaries) is not liable for any loss or damage in connection with any online payments made by you by reason of (i) any failure, delay, interruption, suspension or restriction of the transmission of any information or message from any payment gateways of the relevant banks and/or third party merchants for processing credit/debit/smart card or other payment facilitation mechanism; (ii) any negligence, mistake, error in or omission from any information or message transmitted from the said payment gateways; (iii) any breakdown, malfunction or failure of those gateways in effecting online payment service or (iv) anything arisen out of or in connection with the said payment gateways, including but not limited to unauthorised access to or alternation of the transmission of data or any unlawful act not permitted by the law.
1. Cash, EPS, WeChat Pay Or Alipay
Course fees can be paid by cash, EPS, WeChat Pay or Alipay at any HKU SPACE Enrolment Centres.
2. Cheque Or Bank draft
Course fees can also be paid by crossed cheque or bank draft made payable to “HKU SPACE”. Please specify the programme title(s) for application and the applicant’s name.. You may either:
- bring the completed form(s), together with the appropriate course or application fees in the form of a cheque, and any required supporting documents to any of the HKU SPACE enrolment centres;
- or mail the above documents to any of the HKU SPACE Enrolment Centres, specifying “Course Application” on the envelope. HKU SPACE will not be responsible for any loss of payment sent by mail.
Applicants may also pay the course fee by VISA or Mastercard, including the “HKU SPACE Mastercard”, at any HKU SPACE enrolment centres. Holders of the HKU SPACE Mastercard can enjoy a 10-month interest-free instalment period for courses with a tuition fee worth a minimum of HK$2,000; however, the course applicant must also be the cardholder himself/herself. For enquiries, please contact our staff at any enrolment centres.
4. Online Payment
Online application / enrolment is offered for most open admission courses (course enrolled on first come, first served basis) and selected award-bearing programmes. Application fees and course fees of these programmes/courses can be settled by using "PPS by Internet" (not available via mobile phones), VISA or Mastercard. In addition to the aforesaid online payment channels, continuing students of award-bearing programmes, if their programmes offer online service, may also pay their course fees by Online WeChat Pay, Online Alipay and Faster Payment System (FPS). Please refer to Enrolment Methods - Online Enrolment for details.
- If the programme/course is starting within five working days, application by post is not recommended to avoid any delays. Applicants are advised to enrol in person at HKU SPACE Enrolement Centres and avoid making cheque payment under this circustance.
- Fees paid are not refundable except under very exceptional circumstances (e.g. course cancellation due to insufficient enrolment), subject to the School’s discretion. In exceptional cases where a refund is approved, fees paid by cash, EPS, WeChat Pay, Alipay, cheque or PPS (for online payment only) will normally be reimbursed by a cheque, and fees paid by credit card will normally be reimbursed to the payment cardholder's credit card account.
- In addition to the published fees, there may be additional costs associated with individual programmes. Please refer to the relevant course brochures or direct any enquiries to the relevant programme team for details.
- Fees and places on courses cannot be transferrable from one applicant to another. Once accepted onto a course, the student may not change to another course without approval from HKU SPACE. A processing fee of HK$120 will be levied on each approved transfer.
- Receipts will be issued for fees paid but HKU SPACE will not be repsonsible for any loss of receipt sent by mail.
- For payment certification, please submit a completed form, a sufficiently stamped and self-addressed envelope, and a crossed cheque for HK$30 per copy made payable to "HKU SPACE" to any of our enrolment centres.
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